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Financial Asset Management Using Artificial Neural Networks

Author

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  • Roohollah Younes Sinaki

    (Ohio University, USA)

  • Azadeh Sadeghi

    (Ohio University, USA)

  • Dustin S. Lynch

    (Ohio University, USA)

  • William A. Young II

    (Ohio University, USA)

  • Gary R. Weckman

    (Ohio University, USA)

Abstract

Investors typically build portfolios for retirement. Investment portfolios are typically based on four asset classes that are commonly managed by large investment firms. The research presented in this article involves the development of an artificial neural network-based methodology that investors can use to support decisions related to determining how assets are allocated within an investment portfolio. The machine learning-based methodology was applied during a time period that included the stock market crash of 2008. Even though this time period was highly volatile, the methodology produced desirable results. Methodologies such as the one presented in this article should be considered by investors because they have produced promising results, especially within unstable markets.

Suggested Citation

  • Roohollah Younes Sinaki & Azadeh Sadeghi & Dustin S. Lynch & William A. Young II & Gary R. Weckman, 2020. "Financial Asset Management Using Artificial Neural Networks," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 11(3), pages 66-86, July.
    • Handle: RePEc:igg:joris0:v:11:y:2020:i:3:p:66-86
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